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The Effect of Rural Inequality

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The Effect of Rural Inequality THE EFFECT OF RURAL INEQUALITY ON FERTILITY, MIGRATION, ENVIRONMENT AND THUS AGRICULTURAL SUSTAINABILITY: A CASE STUDY IN THE ARID AND SEMI-ARID AREAS IN THE NORTHERN PROVINCE OF SOUTH AFRICA: FINAL REPORT: 17 April 2002, amended 10 May Johann Kirsten, Juliana Rwelamira, Frances Fraser and Moraka Makhura 1. INTRODUCTION This chapter, which is in essence descriptive, reports the results of the survey of land and asset size, structure and distribution, and of some possibly related demographic and environmental circumstances, in Northern Province (NP) (recently renamed to Limpopo Province), South Africa. First, however, for readers to interpret these results and compare them with the other two country surveys in this study, we must explain the basic social indicators of the country (see Table 1), the unusual forms of inequality, poverty, asset ownership, rural and agricultural activity, and unemployment in South Africa. Table 1: Social indicators for South Africa (1996/97/98) Indicator South Africa Northern Province Population (Census, 1996) 40.58 million 4.93 million Population growth rate 2.08 % 2.31% Urban population as % of total 53.70% 10.95% Infant mortality rate 41 53 Total fertility rate 2.7 3.2 % of population < 15yrs 34.33% 42.75% Life expectancy at birth 63 63 Non-urban economic active population as 32.9% 82.8% percentage of total economic active population Total unemployment rate (See footnote 3 on p3) 33.8% 45.9% Doctors per 10 000 population 2.9 1.5 Hospital beds per 1 000 population 4.0 3.1 Diseases1: % of HIV infected women at antenatal clinics 22.8% 11.5% TB cases per 100 000 population - 286 Malaria cases per 100 000 population 22 950 4 814 Tuberculosis cases per 100 000 population 63 136 1 947 Typhoid cases per 100 000 population 425 98 Viral hepatitis cases per 100 000 population 1 042 109 Human Development Index 0.672 0.566 Gini coefficient (for income) 65 66 Infrastructure: % households with access to electricity 57.3% 36.2% % households with access to piped water 79.8% 75.5% % households with access to sanitation 82.5% 77.8% % households with access to telephones 28.6% 7.4% Source: DBSA Development Report 2000 In purchasing power parity dollars of 1993, South Africa has a mean income of $7450 in 1996 (World Bank, 1998). This places the country well up the ranks of lower middle-income countries. Yet in 1998, 11.5 per cent of South Africans consumed less 1 The lower figures for the Northern Province could perhaps be attributed to lower population density and possibly under reporting in remote areas. 1 than a dollar's worth per person per day of a standard 1993 consumption bundle, and 35.8 per cent consumed less than $2/day (World Bank 2000/2001). Such significant incidence of abject poverty is usually found only in countries with much lower mean income per person. It is possible at South Africa's higher level due to extreme inequality - overall (in terms of income Gini coefficients), regional, ethnic, and rural- urban. 2 Pervading this survey (this chapter) and relating it to the study as a whole, extreme inequality converts adequate average income in South Africa into pervasive rural poverty in mainly African areas of rural Northern Province via: · low and unequal land and asset endowment; · high local unemployment (worse in rural areas, NP, and among Africans); · heavy reliance on migrancy and transfer incomes; · high fertility, child/adult ratios and household size among low-income groups. Poverty: Several estimates of levels of poverty using different poverty lines and databases have been done in South Africa. DBSA [2000] using census data and a poverty line of R800 household expenditure per month estimates that about 57 per cent of South Africans are living in poverty while around 78% of the population in the Northern Province are considered to be poor. In Table 2 we compare the poverty calculations of May (1998) with that of the DBSA. With a somewhat different poverty line of R352 per adult equivalent (AE) per month, May (1998) found that 50% of the South African population can be classified as poor while he estimates a poverty rate of 62% in the Northern Province. Table 3 further shows poverty incidence in the districts of the Northern Province. Table 2: Comparative statistics on poverty measurements in South Africa May, J. 1998 (for 1995) DBSA 2000 (for 1996) Poverty line % Poor Poverty Line % poor South Africa R352/AE/month R800 per HH per month All 49.9%* 56.9% Rural 70.9% - Urban 28.5% - Northern Province R352/AE/month R800 per HH per month All 61.9% 77.9% Rural - - Urban - - Sources: DBSA, 2000 (pp176) and May, J. (1998) (pp) * = the CSS (1995) estimates that 60.7% of Africans live in poverty according to the R352/AE poverty line 2 The dimensions of inequality are related, e.g. the poorest ethnic group (African) is heavily over- represented in the poorest areas (e.g. the eastern Cape) and in rural regions. 2 Table 3: Poverty head count ratio for selected districts in the Northern Province (based on consumption expenditure of R800 per month per household at 1996 prices) Magisterial District Headcount ratio Imputed mean household expenditure Bochum* 44% R1 306 Sekhukuneland* 42% R1 399 Sekgosese 41% R1 423 Nebo 39% R1 502 Mokerong* 36% R1 648 Potgietersrus 32% R3 358 Pietersburg 14% R7 577 Seshego* 34% R1 883 Source: Statistics South Africa, 2000. Measuring poverty in South Africa * Districts where survey was undertaken Unemployment: According to the results of the 1996 Census the South African population is estimated at 40,584 million with population growth slowing to about 2 percent per annum – down from 2.5% per annum during the 1980s. The high levels of unemployment in South Africa in general can partly explain the high poverty rates referred to above. The Census results indicate that total employment in the economy is 9 114 000, of which about 1 800 000 are informal job opportunities. About 33.8 percent of the economically active population is unemployed3 (and seeking work) numbering about 2 million work seekers. The rural unemployment rate for South Africa is 44.2% (Urban = 28.7%) and 50.5% for the Northern Province (23.7 % for urban areas). In South Africa youth unemployment makes up 48.5% of total unemployment (43.8% in the Northern Province). Growing youth unemployment is a major challenge, impacting on crime trends and threatening the integrity of family and community structures. The census confirms that the unemployment burden falls disproportionately on black men and women under the age of 35 and is particularly severe in rural areas. The employment challenge has been the focus of concerted deliberations of government, business, labour and community representatives. 3 The DBSA (2000:193) used the following definition for unemployment: Persons 15 years of age and older who, during the reference week, were not in paid work or self-employment, were available for paid work or self-employment, took specific steps during the four weeks preceding the interview to find paid work or self-employment, or had the desire to work and were available to take up a suitable job if one was offered. 3 Table 4: A profile of the population in the Northern Province Characteristics Northern Province Population size 4.93 million § Males (%) 45.5% § Females (%) 54.5% § Urban 10.9% § Non-Urban 89.1% § Urban Males 12.4% § Non-Urban Males 87.6% § Urban Females 11.4% § Non-Urban Females 88.6% Most Important Source of Income (%) § Wages 43.1% § Pension 27.1% § Remittances 21.5% § Farming 2.2% § Other 6.1% Household Income in the Month prior to the survey (%) (1997 prices) § R1501 or More 10.1% § R801-R1500 20.6% § R401-R800 33.1% § R400 or less 36.2% Source: Statistics South Africa. Population Census 1996; Statistics South Africa. Rural Survey 1997 2. THE STUDY AREA AND SAMPLE DESIGN 2.1 The Study Area The Northern Province (Limpopo Province) was selected as the study area for the South African case study of this multi-country research programme. As indicated earlier this province is also one of the poorest provinces in South Africa. Selecting the households from this province for studying demographic behaviour posed a serious problem for the research team due to the racial composition of South Africa. We know that inequality is much more profound between race groups (due to the apartheid legacy) and that the wealthiest South Africans are mostly Whites, living outside the former "homelands" areas. For reasons of logistics, however, we decided to survey only such areas. This more focused approach would through careful interpretation allow us to answer the various research questions. Our findings will allow us to explore our main concern - the likely effect of enhancing the land or other assets of the rural poor upon their fertility, migration, and environmental management. We shall be able to compare such behaviour among households in our survey with different amounts of land or other assets (or with different histories of change in the amount of assets), and among villages with different degrees of internal land and asset inequality. Sections 6 and 7 report the differences in, respectively, migration (6) and fertility (7), among households and villages currently endowed with different amounts of land or other assets. This permits (cautious and tentative) inferences about how such behaviour might change, if part of the large concentrations of assets (including 4 farmland), available elsewhere in Northern Province, were distributed to various groups in the villages surveyed. The Northern Province is situated in the far northern part of South Africa.
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